The availability of multiple ecological time series linked to both physical and chemical supporting data – as afforded by ECN – increasingly provides opportunities to test existing, and develop new, indicators of environmental and ecological change and resilience

The availability of multiple ecological time series linked to both physical and chemical supporting data – as afforded by ECN – increasingly provides opportunities to test existing, and develop new, indicators of environmental and ecological change and resilience.

Indicators are required to quantify the extent to which species population sizes and community structure are affected by climate change, in order to inform climate change impact assessments.

The authors developed a new community-based climate change indicator approach to assess climate impacts on moths and butterflies. Rather than using spatial relationships between species distributions and climate, this approach exploits temporal relationships between species abundance and climate.

The approach was tested using data from ECN sites, where lepidopteran communities and weather parameters are measured in close proximity. It was effective at predicting spatial and temporal variation in lepidopteran communities at the sites but only when models were calibrated at a seasonal scale, thus emphasising the need, in this case, to take seasonality into account.